Identifying Interesting Visitors Through Transductive Support Vector Machine Web Log Classifier
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Abstract
Log file data can provide precious insight into web usage mining. Web access log analysis is to analyze the patterns of web site usage and the features of user behavior. Visitors’ characteristics of a web site are analyzed after the sessions are constructed using web log. This paper simplifies the method of classifying interesting users from a given set of web logs of an e-commerce web server. Users are classified into two categories; (1). Users who are really interested in the buying the product, (2). Users who simply browse the site just to get familiarize about the site. Transductive Support Vector Machine (TSVM) algorithm is used to classify the web logs into these two categories of users
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